def test_localize_peaks():
repo = 'https://gin.g-node.org/NeuralEnsemble/ephy_testing_data'
remote_path = 'mearec/mearec_test_10s.h5'
local_path = download_dataset(repo=repo,
remote_path=remote_path,
local_folder=None)
recording = MEArecRecordingExtractor(local_path)
peaks = detect_peaks(recording,
method='locally_exclusive',
peak_sign='neg',
detect_threshold=5,
n_shifts=2,
chunk_size=10000,
verbose=False,
progress_bar=False)
peak_locations = localize_peaks(recording,
peaks,
method='center_of_mass',
chunk_size=10000,
verbose=True,
progress_bar=False)
assert peaks.size == peak_locations.shape[0]
peak_locations = localize_peaks(recording,
peaks,
method='monopolar_triangulation',
n_jobs=1,
chunk_size=10000,
verbose=True,
progress_bar=True)
assert peaks.size == peak_locations.shape[0]
def test_detect_peaks():
repo = 'https://gin.g-node.org/NeuralEnsemble/ephy_testing_data'
remote_path = 'mearec/mearec_test_10s.h5'
local_path = download_dataset(repo=repo,
remote_path=remote_path,
local_folder=None)
recording = MEArecRecordingExtractor(local_path)
peaks = detect_peaks(recording,
method='by_channel',
peak_sign='neg',
detect_threshold=5,
n_shifts=2,
chunk_size=10000,
verbose=1,
progress_bar=False,
outputs='numpy_compact')
sample_inds, chan_inds, amplitudes, seg_inds = detect_peaks(
recording,
method='locally_exclusive',
peak_sign='neg',
detect_threshold=5,
n_shifts=2,
chunk_size=10000,
verbose=1,
progress_bar=False,
outputs='numpy_split')
def test_estimate_motion_rigid():
local_path = download_dataset(repo=repo,
remote_path=remote_path,
local_folder=None)
recording = MEArecRecordingExtractor(local_path)
print(recording)
peaks = np.load('mearec_detected_peaks.npy')
motion, temporal_bins, spatial_bins, extra_check = estimate_motion(
recording,
peaks,
peak_locations=None,
direction='y',
bin_duration_s=1.,
bin_um=10.,
margin_um=5,
method='decentralized_registration',
method_kwargs={},
non_rigid_kwargs=None,
output_extra_check=True,
progress_bar=True,
verbose=True)
# print(motion)
# print(extra_check)
print(spatial_bins)
assert spatial_bins is None
def test_detect_peaks():
repo = 'https://gin.g-node.org/NeuralEnsemble/ephy_testing_data'
remote_path = 'mearec/mearec_test_10s.h5'
local_path = download_dataset(repo=repo,
remote_path=remote_path,
local_folder=None)
recording = MEArecRecordingExtractor(local_path)
# by_channel
peaks = detect_peaks(recording,
method='by_channel',
peak_sign='neg',
detect_threshold=5,
n_shifts=2,
chunk_size=10000,
verbose=1,
progress_bar=False)
# by_channel
sorting = detect_peaks(recording,
method='by_channel',
peak_sign='neg',
detect_threshold=5,
n_shifts=2,
chunk_size=10000,
verbose=1,
progress_bar=False,
outputs="sorting")
assert isinstance(sorting, BaseSorting)
# locally_exclusive
peaks = detect_peaks(recording,
method='locally_exclusive',
peak_sign='neg',
detect_threshold=5,
n_shifts=2,
chunk_size=10000,
verbose=1,
progress_bar=False)
# locally_exclusive + localization
peaks = detect_peaks(
recording,
method='locally_exclusive',
peak_sign='neg',
detect_threshold=5,
n_shifts=2,
chunk_size=10000,
verbose=1,
progress_bar=True,
localization_dict=dict(method='center_of_mass',
local_radius_um=150,
ms_before=0.1,
ms_after=0.3),
#localization_dict=dict(method='monopolar_triangulation', local_radius_um=150,
# ms_before=0.1, ms_after=0.3, max_distance_um=1000)
)
assert 'x' in peaks.dtype.fields
def test_localize_peaks():
repo = 'https://gin.g-node.org/NeuralEnsemble/ephy_testing_data'
remote_path = 'mearec/mearec_test_10s.h5'
local_path = download_dataset(repo=repo, remote_path=remote_path, local_folder=None)
recording = MEArecRecordingExtractor(local_path)
peaks = detect_peaks(recording,
method='by_channel',
peak_sign='neg', detect_threshold=5, n_shifts=2,
chunk_size=10000, verbose=False, progress_bar=False,
outputs='numpy_compact'
)
peak_locations = localize_peaks(recording, peaks,
chunk_size=10000, verbose=True, progress_bar=False, )
assert peaks.size == peak_locations.shape[0]
def test_motion_functions():
local_path = download_dataset(repo=repo,
remote_path=remote_path,
local_folder=None)
recording = MEArecRecordingExtractor(local_path)
peaks = np.load('mearec_detected_peaks.npy')
bin_um = 2
motion_histogram, temporal_bins, spatial_bins = make_motion_histogram(
recording, peaks, bin_um=bin_um)
# print(motion_histogram.shape, temporal_bins.size, spatial_bins.size)
pairwise_displacement = compute_pairwise_displacement(motion_histogram,
bin_um,
method='conv2d')
motion = compute_global_displacement(pairwise_displacement)
def test_detect_peaks():
repo = 'https://gin.g-node.org/NeuralEnsemble/ephy_testing_data'
remote_path = 'mearec/mearec_test_10s.h5'
local_path = download_dataset(repo=repo, remote_path=remote_path, local_folder=None)
recording = MEArecRecordingExtractor(local_path)
# by_channel
noise_levels = get_noise_levels(recording, return_scaled=False)
peaks = detect_peaks(recording, method='by_channel',
peak_sign='neg', detect_threshold=5, n_shifts=2,
chunk_size=10000, verbose=1, progress_bar=False, noise_levels=noise_levels)
subset_peaks = select_peaks(peaks, max_peaks_per_channel=100)
subset_peaks = select_peaks(peaks, 'smart_sampling', max_peaks_per_channel=100, noise_levels=noise_levels)
assert len(subset_peaks) < len(peaks)
def setup_module():
local_path = download_dataset(repo=repo,
remote_path=remote_path,
local_folder=None)
recording = MEArecRecordingExtractor(local_path)
# detect and localize
peaks = detect_peaks(
recording,
method='locally_exclusive',
peak_sign='neg',
detect_threshold=5,
n_shifts=2,
chunk_size=10000,
verbose=1,
progress_bar=True,
localization_dict=dict(method='center_of_mass',
local_radius_um=150,
ms_before=0.1,
ms_after=0.3),
#~ localization_dict=dict(method='monopolar_triangulation', local_radius_um=150, ms_before=0.1, ms_after=0.3, max_distance_um=1000),
)
np.save('mearec_detected_peaks.npy', peaks)